1. Analysis of Technical Trends Ryan Weikert

2. Asset Valuation Pricing, Buying, and Selling of Assets Methods of Appraisal What stocks, when? Fundamental Analysis Technical Analysis

3. Fundamental Analysis Quality Sector/Industry Financial Statements Peer and Historical Comparisons Earnings Management Fair Value

4. Technical Analysis Study trends and the state of the market Behavioral Indicators Anticipate price movements

5. Examples Support/Resistance Levels Moving Averages and Momentum Overbought and Oversold Signals Buy and Sell

6. Is it possible to earn greater profits using pure technical analytics?

7. Process Generate Random Walks Geometric Brownian Motion Apply certain technical indicators to these random walks Generate buy and sell signals Record asset price at the time of those signals Calculate profit

8. Moving Average Convergence Divergence (MACD) Signals upward and downward momentum Exponential Moving Average (EMA) X i =(P i - X i-1 )*[2/(# of periods + 1)]+X i-1 MACD=12 day EMA – 26 day EMA Signal Line=9 day EMA MACD MACD Histogram = MACD – Signal Line Buy if MACD Histogram > 0 (upward momentum) Sell if MACD Histogram < 0 (downward momentum)

9. Apple MACD Chart

10. MACD Results E(profit) ≈ ½ (mu)(S 0 ) SD ≈ 2/3 (sigma)(S 0 ) If mu =.08, S 0 = 100, sigma=.3 – E(profit)=3.95 – SD = 22.15 ½ expected profit of a long position Only slightly less risk Inferior

11. Distribution

12. Relative Strength Index (RSI) Overbought and Oversold signals RSI = 100 – 100/(1+Relative Strength) Relative Strength = Average Gain/Average Loss Ag i = [Ag i-1 * 13 + current gain] / 14 0<RSI<100 Oversold if RSI <30  Buy Overbought if RSI >70  Sell

13. BBVA RSI Chart

14. RSI Results – Perfect Timing S0100 mu0.080.04-0.020.08 sigma0.3 0.1 mean29.0829.1728.639.28 sd21.3720.9720.647.42 lb28.66 28.239.13 ub29.50 29.049.43 E(profit) ≈ sigma* S 0

15. Distribution

16. RSI Results – Quick Trigger E(profit) ≈ 0 S0100 mu0.080.02-0.020.08 sigma0.3 0.1 mean-1.32-0.020.23-2.68 sd25.6923.6822.469.836 lb-1.83-0.48-0.20-2.87 ub-0.820.440.67-2.49

17. Distribution Histogram of profit profit Frequency -200-150-100-50050 0 1000 2000 3000 4000

18. Overall RSI Results Further technical analysis would be required Impossible to receive returns of Perfect Investor – If it were possible, technical indicators wouldn’t be needed Expected profit won’t be as high Closer to 0

19. Commodity Channel Index (CCI) Overbought and Oversold signals CCI = (Typical Price – 20 day SMA of TP) (.015 * Mean Deviation) TP = (High + Low + Close)/3 Overbought if CCI > 100  Sell Oversold if CCI < -100  Buy

20. Apple CCI Chart

21. Results Similar to RSI Perfect Timing – E(profit) ≈ 2*sigma*S 0 – SD ≈ 2/3 * sigma Quick Trigger – E(profit) ≈ 0 – SD ≈ 2/3 * sigma

23. CCI Conclusion Still impossible to attain perfect timing Expected profit likely to be closer to 0

24. Conclusion Technical analysis Geometric Brownian Motion Not useful

25. Upcoming What must be true for these indicators to yield a statistically significant profit? Other Distributions – How are real world returns distributed? – How do they vary in different situations? Other Processes – Autoregressive process – Lévy Process Applied to actual graphs

26. Questions?